Hyperspectral Image Analysis | Taschenbuch

Cover: 9783030386191 | Hyperspectral Image Analysis | Jocelyn Chanussot (u. a.) | Taschenbuch

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Sprache: Englisch

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Beschreibung

This book reviews the state of the art in algorithmic approaches addressing the practical challenges that arise with hyperspectral image analysis tasks, with a focus on emerging trends in machine learning and image processing/understanding. It presents advances in deep learning, multiple instance learning, sparse representation based learning, low-dimensional manifold models, anomalous change detection, target recognition, sensor fusion and super-resolution for robust multispectral and hyperspectral image understanding. It presents research from leading international experts who have made foundational contributions in these areas. The book covers a diverse array of applications of multispectral/hyperspectral imagery in the context of these algorithms, including remote sensing, face recognition and biomedicine. This book would be particularly beneficial to graduate students and researchers who are taking advanced courses in (or are working in) the areas ofimage analysis, machine learning and remote sensing with multi-channel optical imagery. Researchers and professionals in academia and industry working in areas such as electrical engineering, civil and environmental engineering, geosciences and biomedical image processing, who work with multi-channel optical data will find this book useful.

Über den Autor

Dr. Saurabh Prasad is an Associate Professor at the Department of Electrical and Computer Engineering at the University of Houston, TX, USA.

Dr. Jocelyn Chanussot is a Professor in the Signal and Images Department at Grenoble Institute of Technology, France.

Zusammenfassung

Provides a comprehensive review of the state of the art in hyperspectral image analysis

Presents perspectives from experts who are pioneers in a broad range of signal processing and machine learning fields related to hyperspectral imaging and remote sensing

Is suitable both as a reference book and as a textbook for advanced graduate courses on multi-dimensional image processing

Inhaltsverzeichnis

1. Introduction.- 2. Machine Learning Methods for Spatial and Temporal Parameter Estimation.- 3. Deep Learning for Hyperspectral Image Analysis, Part I: Theory and Algorithms.- 4. Deep Learning for Hyperspectral Image Analysis, Part II: Applications to Remote Sensing and Biomedicine.- 5. Advances in Deep Learning for Hyperspectral Image Analysis - Addressing Challenges Arising in Practical Imaging Scenarios.- 6. Addressing the Inevitable Imprecision: Multiple Instance Learning for Hyperspectral Image Analysis.

Details

Erscheinungsjahr:	2021
Fachbereich:	Anwendungs-Software
Genre:	Informatik , Mathematik , Medizin , Naturwissenschaften , Technik
Rubrik:	Naturwissenschaften & Technik
Medium:	Taschenbuch
Inhalt:	vi 466 S. 26 s/w Illustr. 144 farbige Illustr. 466 p. 170 illus. 144 illus. in color.
ISBN-13:	9783030386191
ISBN-10:	3030386198
Sprache:	Englisch
Einband:	Kartoniert / Broschiert
Redaktion:	Chanussot, Jocelyn Prasad, Saurabh
Herausgeber:	Saurabh Prasad/Jocelyn Chanussot
Auflage:	1st edition 2020
Hersteller:	Springer Nature Switzerland Springer International Publishing
Verantwortliche Person für die EU:	Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com
Maße:	235 x 155 x 26 mm
Von/Mit:	Jocelyn Chanussot (u. a.)
Erscheinungsdatum:	29.04.2021
Gewicht:	0,709 kg

Artikel-ID: 119758089